Analysis of Social Network Data Mining for Security Intelligence Privacy Machine Learning

Article Sidebar

PDF
Published: Aug 18, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i8s.7185
Keywords:
Data mining, Privacy, Machine Learning, Internet platform, Security, social media

Main Article Content

S. Elango
Assistant Professor, Dept of CSE, Madanapalle Institute of Technology & Science, Madanapalle, Andhra Pradesh
V Revathi
Professor, Department of Physics, Applied Sciences, New Horizon College of Engineering, Bangalore, Karnataka, India
S. Aruna Deepthi
Assistant Professor, ECE, Vasavi college of Engineering, Hyderabad
Ananya Bhargavi Kodali
UG Student -Computer Science, Arizona State University, Arizona, USA
M. Gopila
AP(Sr.G), Electrical and Electronics Engineering, Sona college of Technology, Sona Nagar, Salem
Bibin K Jose
Associate Professor, PG & Research Department of Mathematics, Sanatana Dharma College Alappuzha, Kerala, India

Abstract

The Modern communication on the Internet platform is most responsive through social media. Social media has changed and is still reshaping how we share our thoughts and emotions in communication. It has introduced a constant real-time communication pattern that was before unheard of. Young and old, organizations, governmental agencies, professional associations, etc., all have social media accounts that they use exclusively for communication with other users. Social media also acts as a powerful network engine that connects users regardless of where they are in the world. The development of global communication will greatly benefit from the availability of this new communication platform in the future. Consequently, there is a pressing need to research usage trends. Therefore, it is vital to investigate social media platform usage trends in order to develop automated systems that intelligence services can use to help avert national security incidents. Through the use of social media data mining, this research study suggests an automated machine learning model that can improve speedy response to crises involving national and International security.

Article Details

How to Cite
Elango, S. ., Revathi, V. ., Deepthi, S. A. ., Kodali, A. B. ., Gopila, M. ., & Jose, B. K. . (2023). Analysis of Social Network Data Mining for Security Intelligence Privacy Machine Learning. International Journal on Recent and Innovation Trends in Computing and Communication, 11(8s), 155–161. https://doi.org/10.17762/ijritcc.v11i8s.7185
Issue
Vol. 11 No. 8s (2023)
Section
Articles

References

de Leeuw, AW., Heijboer, M., Verdonck, T. et al. Exploiting sensor data in professional road cycling: personalized data-driven approach for frequent fitness monitoring. Data Min Knowl Disc 37, 1125–1153 (2023). https://doi.org/10.1007/s10618-022-00905-5

Ziyu, Z., Kuang, K., Li, B. et al. Differentiated matching for individual and average treatment effect estimation. Data Min Knowl Disc 37, 205–227 (2023). https://doi.org/10.1007/s10618-022-00886-5

R. Josphineleela, S. Kaliappan, L. Natrayan and A. Garg, "Big Data Security through Privacy – Preserving Data Mining (PPDM): A Decentralization Approach," 2023 Second International Conference on Electronics and Renewable Systems (ICEARS), Tuticorin, India, 2023, pp. 718-721, doi: 10.1109/ICEARS56392.2023.10085646.

T. C. S. Lakshmi, R. A. A. Rosaline, R. T. Selvi, D. Karunkuzhali and S. Lavanya, "Privacy-Preserving Data Mining Process in Industry," 2023 International Conference on Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), Bengaluru, India, 2023, pp. 834-839, doi: 10.1109/IITCEE57236.2023.10091069.

K. N. Prasanthi, C. Sekhara Rao Mvp and S. B. Pallapothu, "Boosted Hybrid Privacy Preserving Data Mining (BHPPDM) Technique to Increase Privacy and Accuracy," 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), Coimbatore, India, 2023, pp. 378-384, doi: 10.1109/ICAIS56108.2023.10073804.

Ana Oliveira, Yosef Ben-David, Susan Smit , Elena Popova, Milica Mili?. Machine Learning for Decision Optimization in Complex Systems. Kuwait Journal of Machine Learning, 2(3). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/201

M. Rafiei and W. M. P. Van Der Aalst, "An Abstraction-Based Approach for Privacy-Aware Federated Process Mining," in IEEE Access, vol. 11, pp. 33697-33714, 2023, doi: 10.1109/ACCESS.2023.3263673.

Suryawanshi, R. ., & Vanjale, S. . (2023). Brain Activity Monitoring for Stress Analysis through EEG Dataset using Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 11(1s), 236–240. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2498

P. A., G. V. Reddy and G. Ramachandran, "Artificial Intelligence Techniques for the wireless wearable Smart Healthcare Prediction System Applications," 2023 Second International Conference on Electronics and Renewable Systems (ICEARS), Tuticorin, India, 2023, pp. 879-884, doi: 10.1109/ICEARS56392.2023.10085051.

Bandara, E., Liang, X., Shetty, S. et al. Octopus: privacy preserving peer-to-peer transactions system with InterPlanetary file system (IPFS). Int. J. Inf. Secur. 22, 591–609 (2023). https://doi.org/10.1007/s10207-022-00650-2

A. V. Kumar, K. Monica and K. Mandadi, "Data Privacy Over Cloud Computing using Multi Party Computation," 2023 International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT), Bengaluru, India, 2023, pp. 262-267, doi: 10.1109/IDCIoT56793.2023.10053427.

Lovren?i?, R., Škvorc, D. Multi-cloud applications: data and code fragmentation for improved security. Int. J. Inf. Secur. 22, 713–721 (2023). https://doi.org/10.1007/s10207-022-00658-8

P. A. Padmaavathy, A. Celina, R. P. Devi, B. N. Arathi, G. Sureshkumar and G. Ramachandran, "Analysis Techniques for Pharmaceutical Drugs Biomedicine Big Data Analytics and Machine Learning," 2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS), Madurai, India, 2023, pp. 83-86, doi: 10.1109/ICICCS56967.2023.10142645.

Mishra, K.C., Dutta, S. A simple and secure user authentication scheme using Map Street View with usability analysis based on ISO/IEC 25022. Int. J. Inf. Secur. 22, 403–415 (2023). https://doi.org/10.1007/s10207-022-00636-0

A. Padma, S. Gadde, B. S. P. Rao and G. Ramachandran, "Effective Cleaning System management using JSP and Servlet Technology," 2021 6th International Conference on Communication and Electronics Systems (ICCES), Coimbatre, India, 2021, pp. 1472-1478, doi: 10.1109/ICCES51350.2021.9488925.

P. Kumar Goswami, S. Baruah and L. Thakuria, "Cyber Security and Data Mining Techniques," 2022 International Conference on Edge Computing and Applications (ICECAA), Tamilnadu, India, 2022, pp. 1427-1431, doi: 10.1109/ICECAA55415.2022.9936489.

P. A., B. Seth and G. Ramachandran, "Analysis of Current Smart Wearable Trends using Internet of Medical Things," 2023 Third International Conference on Artificial Intelligence and Smart Energy (ICAIS), Coimbatore, India, 2023, pp. 19-22, doi: 10.1109/ICAIS56108.2023.10073832.

R. N. Yasa, I. K. S. Buana, Girinoto, H. Setiawan and R. B. Hadiprakoso, "Modified RNP Privacy Protection Data Mining Method as Big Data Security," 2021 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS, Jakarta, Indonesia, 2021, pp. 30-34, doi: 10.1109/ICIMCIS53775.2021.9699180.

H. Chen, "Construction of Network Information Security Risk Framework Based on Data Mining and Analysis," 2022 International Conference on Artificial Intelligence of Things and Crowdsensing (AIoTCs), Nicosia, Cyprus, 2022, pp. 185-189, doi: 10.1109/AIoTCs58181.2022.00035.

T. Soewu, Hemant, M. Rakhra and D. Singh, "Analysis of Data Mining-Based Approach for Intrusion Detection System," 2022 5th International Conference on Contemporary Computing and Informatics (IC3I), Uttar Pradesh, India, 2022, pp. 908-912, doi: 10.1109/IC3I56241.2022.10072828.

W. Deng, Z. Huang, J. Zhang and J. Xu, "A Data Mining Based System For Transaction Fraud Detection," 2021 IEEE International Conference on Consumer Electronics and Computer Engineering (ICCECE), Guangzhou, China, 2021, pp. 542-545, doi: 10.1109/ICCECE51280.2021.9342376.

S. M et al., "Analysis of Hydroponic System Crop Yield Prediction and Crop IoT-based monitoring system for precision agriculture," 2022 International Conference on Edge Computing and Applications (ICECAA), Tamilnadu, India, 2022, pp. 575-578, doi: 10.1109/ICECAA55415.2022.9936473.

S. M. Ar?kan and S. Acar, "A Data Mining Based System for Automating Creation of Cyber Threat Intelligence," 2021 9th International Symposium on Digital Forensics and Security (ISDFS), Elazig, Turkey, 2021, pp. 1-7, doi: 10.1109/ISDFS52919.2021.9486335.

Y. Huang and W. Zhang, "Research on the Methods of Data Mining based on the Edge Computing for the IoT," 2023 IEEE International Conference on Integrated Circuits and Communication Systems (ICICACS), Raichur, India, 2023, pp. 1-6, doi: 10.1109/ICICACS57338.2023.10099991.

A. Vaghela and A. Suthar, "Comprehensive Analysis of Privacy and Data Mining Techniques," 2022 6th International Conference On Computing, Communication, Control And Automation (ICCUBEA, Pune, India, 2022, pp. 1-6, doi: 10.1109/ICCUBEA54992.2022.10010944.